• DocumentCode
    750093
  • Title

    Comments, with reply, on "Fast convolution with Laplacian-of-Gaussian masks" by J.S. Chen et al

  • Author

    Sotak, G.E. ; Boyer, Kim L. ; Chen, Jim S. ; Huertas, Andres ; Medioni, Gerard

  • Author_Institution
    Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
  • Volume
    11
  • Issue
    12
  • fYear
    1989
  • Firstpage
    1329
  • Lastpage
    1332
  • Abstract
    In a recent paper by J.S. Chen et al. (ibid., vol.PAMI-9, p.584-90, July 1987) the authors presented a means of decomposing the Laplacian-of-Gaussian (LoG) kernel into the product of a Gaussian and a (smaller) LoG mask. They then proceeded to develop a fast algorithm for convolution which exploits the spatial frequency properties of these operators to allow the image to be decimated (subsampled). Although this approach is both novel and interesting, it is contended that the exposition suffers from some inconsistencies and minor errors. The commenters clarify matters for those who wish to implement this technique. The original authors acknowledge two of the three points raised, and provide further clarification of the other one namely, the claim that the masks (Gaussian and LoG) are too small.<>
  • Keywords
    pattern recognition; picture processing; Laplacian-of-Gaussian masks; convolution; decimation; fast kernel; subsampling; Calendars; Context modeling; Convolution; Gray-scale; Image segmentation; Parameter estimation; Pattern recognition; Remote sensing; Statistical analysis; Testing;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.41372
  • Filename
    41372